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oft_setting2_chunksize25_batch32_20k
AAyano/oft_setting2_chunksize25_batch32_20k
oft_setting2_chunksize25_batch32_20k is a robotics model from AAyano. Use it for the robotics task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as mit.
OpenVLA-OFT checkpoint fine-tuned on real-world XArm data, setting 2: cup stacking. Intermediate checkpoint at 20000 / 30000 training steps (see oftsetting2chunksize25batch32 for the final 30k-step model). LoRA weight…
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At a glance
- Task
- Robotics
- Library
- transformers
- License
- mit
- Model type
- openvla
- Access
- Public
- Created
- Jul 9, 2026
- Updated
- Jul 9, 2026
- SHA
- f1aa77ef
Base models
Model card
From the Hugging Face model README
oft_setting2_chunksize25_batch32_20k
OpenVLA-OFT checkpoint fine-tuned on real-world XArm data, setting 2: cup stacking. Intermediate checkpoint at 20000 / 30000 training steps (see oft_setting2_chunksize25_batch32 for the final 30k-step model). LoRA weights (rank 32) are already merged into the openvla/openvla-7b base — this repo is a standalone model.
Training
- Recipe: OpenVLA-OFT (L1 regression, FiLM, parallel decoding)
- Steps: 20000 of 30000 (LR 5e-4, decay after 20000), effective batch size 32
- Action chunk: 25, action dim: 7, proprio dim: 6 (BOUNDS_Q99 normalization)
- Inputs: 2 images (3rd-person + wrist) + proprio
Contents
- Merged model shards (
model-*.safetensors) action_head--20000_checkpoint.pt,proprio_projector--20000_checkpoint.pt,vision_backbone--20000_checkpoint.pt— OFT components needed for deploymentdataset_statistics.json— action/proprio normalization statisticsoft_training_config.json— training configuration snapshot
Use with the openvla-oft codebase; set XArm constants (chunk 25, action dim 7, proprio dim 6) in prismatic/vla/constants.py before deployment.
- Task
- Robotics
- Library
- transformers
- Type
- openvla
- License
- mit
- Created
- Jul 9, 2026
- Updated
- Jul 9, 2026